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To infer cellular-level information from MR signals with high sensitivity and specificity is a challenging task. We previously demonstrated the feasibility of mapping myelin in the mouse brain based on multi-contrast MRI using deep learning, but the results were based on limited histological data and MRI data from separate cohorts. In this study, we acquired serial 2-photon and MRI data from the same mice and trained a neural network for mapping myelin. Our results demonstrated enhanced sensitivity and specificity compared to conventional MRI myelin markers, our previous network, and polynomial fitting.
Liang et al. (Wed,) studied this question.